This is a report of the analysis of gapminder_clean.csv data.
Pearson’s correlation of CO2 emissions and GDP per capita in 1962 was calculated and the resuls are presented below.
##
## Pearson's product-moment correlation
##
## data: mydata_1962$`CO2.emissions.(metric.tons.per.capita)` and mydata_1962$gdpPercap
## t = 25.269, df = 106, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.8934697 0.9489792
## sample estimates:
## cor
## 0.9260817
The correlation of ‘CO2 emissions (metric tons per capita)’ and gdpPercap equals 0.9260817.
The associated p-value equals < 2.2e-16.
| Year | Correlation | |
|---|---|---|
| 2 | 1967 | 0.9387918 |
| 1 | 1962 | 0.9260817 |
| 3 | 1972 | 0.8428986 |
| 5 | 1982 | 0.8166384 |
| 6 | 1987 | 0.8095531 |
| 7 | 1992 | 0.8094316 |
| 8 | 1997 | 0.8081396 |
| 9 | 2002 | 0.8006421 |
| 4 | 1977 | 0.7928336 |
| 10 | 2007 | 0.7204169 |
The correlation between ‘CO2 emissions (metric tons per capita)’ and gdpPercap is the strongest in the year 1967.
In order to assess what is the relationship a one-way ANOVA test was performed. Results are presented below.
## Df Sum Sq Mean Sq F value Pr(>F)
## continent 3 30161255 10053752 9.642 0.000334 ***
## Residuals 21 21895723 1042653
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 234 observations deleted due to missingness
The p-value is low (p < 0.001), it appears that depending on the continent, there is a difference in energy use.
In order to assess what is the relationship a one-way ANOVA test was performed. Results are presented below.
## Df Sum Sq Mean Sq F value Pr(>F)
## continent 4 536 133.9 0.413 0.799
## Residuals 83 26923 324.4
## 171 observations deleted due to missingness
Because of high (>0.05) p-value it is concluded that there is no significant difference between Europe and Asia with respect to ‘Imports of goods and services (% of GDP)’ in the years after 1990.
| Country | Average.population.density | |
|---|---|---|
| 145 | Macao SAR, China | 14732.035 |
| 163 | Monaco | 14089.900 |
| 101 | Hong Kong SAR, China | 5153.057 |
| 209 | Singapore | 4361.500 |
| 88 | Gibraltar | 2622.250 |
| 23 | Bermuda | 1132.780 |
Macao region in China has the highest ‘Population density (people per sq. km of land area)’ across all years. It is equal to 14732.035.
## First measurment was taken in 1962 and last one in 2007.
The table below shows table ordered in descending order by column containing numerical life expectancy increase.
| Country | Life.exp.increase.numerical | Life.exp.increase.percentage | |
|---|---|---|---|
| 150 | Maldives | 36.91615 | 195.9 |
| 24 | Bhutan | 33.19895 | 200.3 |
| 238 | Timor-Leste | 31.08515 | 189.5 |
| 242 | Tunisia | 30.86076 | 171.2 |
| 182 | Oman | 30.82310 | 169.6 |
| 171 | Nepal | 30.59963 | 185.1 |
The table below shows table ordered in descending order by column containing percentage life expectancy increase.
| Country | Life.exp.increase.numerical | Life.exp.increase.percentage | |
|---|---|---|---|
| 24 | Bhutan | 33.19895 | 200.3 |
| 150 | Maldives | 36.91615 | 195.9 |
| 151 | Mali | 25.71346 | 190.1 |
| 238 | Timor-Leste | 31.08515 | 189.5 |
| 171 | Nepal | 30.59963 | 185.1 |
| 84 | Gambia, The | 25.90834 | 179.3 |
In the Maldives life expectancy has grown by 37 years, what is a growth of 196%. In Bhutan life expectancy has grown by 33 years, what is over 200%.